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        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411
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        Tool Citations

        Please remember to cite the tools that you use in your analysis.

        To help with this, you can download publication details of the tools mentioned in this report:

        About MultiQC

        This report was generated using MultiQC, version 1.29

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/MultiQC/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        This report has been generated by the nf-core/funcscan analysis pipeline. For information about how to interpret these results, please see the documentation.
        Report generated on 2025-12-19, 09:22 UTC based on data in: /home/yasemen/School/BacterialGenomics/nf-corePipelines/funcscan/work/33/703d3d157eec5db05e1adcd95cd5bf

        Software Versions

        Software Versions lists versions of software tools extracted from file contents.

        GroupSoftwareVersion
        ABRICATE_RUNabricate1.0.1
        AMPCOMBI2_CLUSTERampcombi2.0.1
        AMPCOMBI2_COMPLETEampcombi2.0.1
        AMPCOMBI2_PARSETABLESampcombi2.0.1
        AMPIRampir1.1.0
        AMPLIFY_PREDICTAMPlify2.0.0
        AMP_DATABASE_DOWNLOADampcombi2.0.1
        AMRFINDERPLUS_RUNamrfinderplus4.0.23
        amrfinderplus-databasenull
        AMRFINDERPLUS_UPDATEamrfinderplus4.0.23
        ANTISMASH_ANTISMASHantismash8.0.1
        ANTISMASH_ANTISMASHDOWNLOADDATABASESantismash8.0.1
        ARGNORM_ABRICATEargnorm0.5.0
        ARGNORM_DEEPARGargnorm0.5.0
        COMBGCcomBGCnull
        DEEPARG_DOWNLOADDATAdeeparg1.0.4
        DEEPARG_PREDICTdeeparg1.0.4
        DEEPBGC_DOWNLOADdeepbgc0.1.31
        DEEPBGC_PIPELINEdeepbgc0.1.31
        prodigal2.6.3
        FARGENEfargene0.1
        GECCO_RUNgecco0.9.10
        GUNZIP_MACREL_ORFSgunzip1.13
        GUNZIP_MACREL_PREDgunzip1.13
        GUNZIP_PYRODIGAL_FAAgunzip1.13
        GUNZIP_PYRODIGAL_FNAgunzip1.13
        GUNZIP_PYRODIGAL_GBKgunzip1.13
        HAMRONIZATION_ABRICATEhamronization1.1.9
        HAMRONIZATION_AMRFINDERPLUShamronization1.1.9
        HAMRONIZATION_DEEPARGhamronization1.1.9
        HAMRONIZATION_RGIhamronization1.1.9
        HAMRONIZATION_SUMMARIZEhamronization1.1.9
        MACREL_CONTIGSmacrel1.4.0
        PYRODIGALpyrodigal3.6.3
        RGI_CARDANNOTATIONrgi6.0.5
        rgi-database4.0.1
        RGI_MAINrgi6.0.5
        rgi-database4.0.1
        SEQKIT_SEQ_LENGTHseqkitv2.9.0
        UNTAR_CARDuntar1.34
        WorkflowNextflow25.10.0
        nf-core/funcscanv3.0.0-gfa9db01

        nf-core/funcscan Methods Description

        Suggested text and references to use when describing pipeline usage within the methods section of a publication.URL: https://github.com/nf-core/funcscan

        Methods

        Data was processed using nf-core/funcscan v3.0.0 (doi: 10.5281/zenodo.7643099) of the nf-core collection of workflows (Ewels et al., 2020), utilising reproducible software environments from the Bioconda (Grüning et al., 2018) and Biocontainers (da Veiga Leprevost et al., 2017) projects.

        The pipeline was executed with Nextflow v25.10.0 (Di Tommaso et al., 2017) with the following command:

        nextflow run nf-core/funcscan -profile docker --input samplesheet.csv --outdir runscanResults --run_amp_screening --run_arg_screening --run_bgc_screening -c ./funcscan.config

        Th.ipelin.se.h.ollowin.ools.reprocessin.nclude.eqKit.She..l.024).nnotatio.a.arrie.u.ith.Pyrodiga.Larrald.022).h.ollowin.ntimicrobia.eptid.creenin.ool.er.sed.MPlif.L..l.022).acre.Santos-Júnio..l.020).mpi.Fingerhu..l.021)..h.utpu.ro.h.ntimicrobia.eptid.creenin.ool.er.tandardise.n.ummarise.it.MPcomb.Ibrahi.n.erel.023).h.ollowin.ntimicrobia.esistanc.en.creenin.ool.er.sed.ARGen.Berglun..l.019).G.Alcoc..l.020).MRfinderplu.Feldgarde..l.021).eepAR.Arango-Argot.018).BRicat.Seeman.020).h.utput.ro.R.creenin.ool.er.ormalize..h.ntibioti.esistanc.ntolog.sin.rgNor.Ugarcin.erovi..l.025).h.utpu.ro.h.ntimicrobia.esistanc.en.creenin.ool.er.tandardise.n.ummarise.it.AMRonizatio.Maguir..l.023).h.ollowin.iosyntheti.en.luste.creenin.ool.er.sed.ntiSMAS.Bli..l.021).eepBG.Hanniga..l.019).ECC.Carrol..l.021).h.utpu.ro.h.iosyntheti.en.luste.creenin.ool.er.tandardise.n.ummarise.it.omBG.Frangenber..l.023).u.tatistic.er.eporte.sin.ultiQ.Ewel..l.016).

        References

        • Di Tommaso, P., Chatzou, M., Floden, E. W., Barja, P. P., Palumbo, E., & Notredame, C. (2017). Nextflow enables reproducible computational workflows. Nature Biotechnology, 35(4), 316-319. doi: 10.1038/nbt.3820
        • Ewels, P. A., Peltzer, A., Fillinger, S., Patel, H., Alneberg, J., Wilm, A., Garcia, M. U., Di Tommaso, P., & Nahnsen, S. (2020). The nf-core framework for community-curated bioinformatics pipelines. Nature Biotechnology, 38(3), 276-278. doi: 10.1038/s41587-020-0439-x
        • Grüning, B., Dale, R., Sjödin, A., Chapman, B. A., Rowe, J., Tomkins-Tinch, C. H., Valieris, R., Köster, J., & Bioconda Team. (2018). Bioconda: sustainable and comprehensive software distribution for the life sciences. Nature Methods, 15(7), 475–476. doi: 10.1038/s41592-018-0046-7
        • da Veiga Leprevost, F., Grüning, B. A., Alves Aflitos, S., Röst, H. L., Uszkoreit, J., Barsnes, H., Vaudel, M., Moreno, P., Gatto, L., Weber, J., Bai, M., Jimenez, R. C., Sachsenberg, T., Pfeuffer, J., Vera Alvarez, R., Griss, J., Nesvizhskii, A. I., & Perez-Riverol, Y. (2017). BioContainers: an open-source and community-driven framework for software standardization. Bioinformatics (Oxford, England), 33(16), 2580–2582. doi: 10.1093/bioinformatics/btx192
        • Shen, W., Sipos, B., & Zhao, L. (2024). SeqKit2: A Swiss army knife for sequence and alignment processing. iMeta, e191. https://doi.org/10.1002/imt2.191
        • Larralde, M. (2022). Pyrodigal: Python bindings and interface to Prodigal, an efficient method for gene prediction in prokaryotes. Journal of Open Source Software, 7(72), 4296. DOI: 10.21105/joss.04296
        • Li...utherland...ammond.. A..ang...aho...ergman...ouston...arren.. L..ong...oang...ameron.. E..elbing.. C.. Birol.. (2022). AMPlify: attentive deep learning model for discovery of novel antimicrobial peptides effective against WHO priority pathogens. BMC genomics.3(1).7. DOI: 10.1186/s12864-022-08310-4
        • Santos-Júnior.. D..an...hao.. M.. Coelho.. P. (2020). Macrel: antimicrobial peptide screening in genomes and metagenomes. PeerJ..10555. DOI: 10.7717/peerj.10555
        • Fingerhut...iller.. J..trugnell.. M..aly.. L.. Cooke.. R. (2021). ampir: an R package for fast genome-wide prediction of antimicrobial peptides. Bioinformatics (Oxford.ngland).6(21).262–5263. DOI: 10.1093/bioinformatics/btaa653
        • Ibrahim.. & Perelo.. (2023). Darcy220606/AMPcombi. DOI: 10.5281/zenodo.7639121
        • Berglund...sterlund...oulund...arathe.. P..arsson... Kristiansson.. (2019). Identification and reconstruction of novel antibiotic resistance genes from metagenomes. Microbiome.(1).2. DOI: 10.1186/s40168-019-0670-1
        • Alcock.. P..aphenya.. R..au...sang.. K..ouchard...dalatmand...uynh...guyen.. V..heng.. A..iu...in.. Y..iroshnichenko...ran.. K..erfalli.. E..asir.. A..loni...peicher.. J..lorescu...ingh...altyn... McArthur.. G. (2020). CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic acids research.8(D1).517–D525. DOI: 10.1093/nar/gkz935
        • Feldgarden...rover...onzalez-Escalona...rye.. G..aendiges...aft.. H..offmann...ettengill.. B..rasad.. B..illman.. E..yson.. H.. Klimke.. (2021). AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance.tress response.nd virulence. Scientific reports.1(1).2728. DOI: 10.1038/s41598-021-91456-0
        • Arango-Argoty...arner...ruden...eath.. S..ikesland... Zhang.. (2018). DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data. Microbiome.(1).3. DOI: 10.1186/s40168-018-0401-z
        • Seemann.. (2020). ABRicate. Github https://github.com/tseemann/abricate.
        • Ugarcina Perovic...amji...hong...uan...aguire...oelho.. P. (2025). argNorm: normalization of antibiotic resistance gene annotations to the Antibiotic Resistance Ontology (ARO).ioinformatics.taf173. DOI: 10.1093/bioinformatics/btaf173
        • Public Health Alliance for Genomic Epidemiology (pha4ge). (2022). Parse multiple Antimicrobial Resistance Analysis Reports into a common data structure. Github. Retrieved October 5.022.rom https://github.com/pha4ge/hAMRonization
        • Blin...haw...ader...zenei...eitz..L..ugustijn..E..ediel-Becerra..D.D..e Crécy-Lagard...oetsier..A..illiams..E..ruz-Morales...ongwas...egurado Luchsinger..E..iermann...orenskaia...douc..M..eijer...erlouw..R..an der Hooft..J.J..iemert...elfrich..J.N..asschelein...orre...hevrette..G..an Wezel..P..edema..H..eber...025. antiSMASH 8.0: extended gene cluster detection capabilities and analyses of chemistry.nzymology.nd regulation. Nucleic Acids Res. 53.32-W38. DOI: 10.1093/nar/gkz654
        • Carroll.. M. .arralde...leck.. S..onnudurai...ilanese...appio Barazzone.. & Zeller.. (2021). Accurate de novo identification of biosynthetic gene clusters with GECCO. bioRxiv DOI: 0.1101/2021.05.03.442509
        • Frangenberg.. Fellows Yates.. A..brahim...erelo... Beber.. E. (2023). nf-core/funcscan: 1.0.0 - German Rollmops - 2023-02-15. https://doi.org/10.5281/zenodo.7643100
        • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. https://doi.org/10.1093/bioinformatics/btw354
        Notes:
        • The command above does not include parameters contained in any configs or profiles that may have been used. Ensure the config file is also uploaded with your publication!
        • You should also cite all software used within this run. Check the "Software Versions" of this report to get version information.

        nf-core/funcscan Workflow Summary

        - this information is collected when the pipeline is started.URL: https://github.com/nf-core/funcscan

        Input/output options

        input
        samplesheet.csv
        outdir
        runscanResults

        Screening type activation

        run_amp_screening
        true
        run_arg_screening
        true
        run_bgc_screening
        true

        AMP: ampcombi2 parsetables

        amp_ampcombi_parsetables_dbevalue
        5

        AMP: ampcombi2 cluster

        amp_ampcombi_cluster_covmode
        0
        amp_ampcombi_cluster_mode
        1

        ARG: AMRFinderPlus

        arg_amrfinderplus_identmin
        -1

        Generic options

        trace_report_suffix
        2025-12-19_10-55-14

        Core Nextflow options

        configFiles
        /home/yasemen/.nextflow/assets/nf-core/funcscan/nextflow.config, /home/yasemen/School/BacterialGenomics/nf-corePipelines/funcscan/./funcscan.config
        containerEngine
        docker
        launchDir
        /home/yasemen/School/BacterialGenomics/nf-corePipelines/funcscan
        profile
        docker
        projectDir
        /home/yasemen/.nextflow/assets/nf-core/funcscan
        revision
        master
        runName
        spontaneous_mccarthy
        userName
        yasemen
        workDir
        /home/yasemen/School/BacterialGenomics/nf-corePipelines/funcscan/work

        MultiQC v1.29 - Written by Phil Ewels, available on GitHub.

        This report uses Plotly, jQuery, jQuery UI, Bootstrap and FileSaver.js.